Shao-Lun Huang | DeepAI

DeepAI AI Chat

Featured Co-authors

Xi Chen
293 publications
Yan Wang
215 publications
Yefeng Zheng
117 publications
Deng Cai
112 publications
Junzhou Huang
106 publications
Jimeng Sun
99 publications
Yi Ma
93 publications
Lin Zhang
88 publications
Shuming Shi
83 publications
Jian Xu
75 publications
Ningyu Zhang
74 publications

∙ 06/20/2023

Personalized Federated Learning with Feature Alignment and Classifier Collaboration

Data heterogeneity is one of the most challenging issues in federated le...

0 Jian Xu, et al. ∙

∙ 05/29/2023

The First and Second Order Asymptotics of Covert Communication over AWGN Channels

This paper investigates the asymptotics of the maximal throughput of com...

0 Xinchun Yu, et al. ∙

∙ 03/11/2023

Stabilizing and Improving Federated Learning with Non-IID Data and Client Dropout

The label distribution skew induced data heterogeniety has been shown to...

0 Jian Xu, et al. ∙

∙ 10/24/2022

Revisiting Sparse Convolutional Model for Visual Recognition

Despite strong empirical performance for image classification, deep neur...

0 Xili Dai, et al. ∙

∙ 05/13/2022

An Information-theoretic Method for Collaborative Distributed Learning with Limited Communication

In this paper, we study the information transmission problem under the d...

0 Xinyi Tong, et al. ∙

∙ 09/29/2021

PAC-Bayes Information Bottleneck

Information bottleneck (IB) depicts a trade-off between the accuracy and...

0 Zifeng Wang, et al. ∙

∙ 09/14/2021

On Distributed Learning with Constant Communication Bits

In this paper, we study a distributed learning problem constrained by co...

0 Xiangxiang Xu, et al. ∙

∙ 09/13/2021

SignGuard: Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering

Gradient-based training in federated learning is known to be vulnerable ...

0 Jian Xu, et al. ∙

∙ 08/24/2021

Maximum Likelihood Estimation for Multimodal Learning with Missing Modality

Multimodal learning has achieved great successes in many scenarios. Comp...

0 Fei Ma, et al. ∙

∙ 07/30/2021

DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient Distributed Learning

Gradient quantization is an emerging technique in reducing communication...

0 Guangfeng Yan, et al. ∙

∙ 02/27/2021

Lifelong Learning based Disease Diagnosis on Clinical Notes

Current deep learning based disease diagnosis systems usually fall short...

0 Zifeng Wang, et al. ∙

∙ 12/17/2020

Predicting Events in MOBA Games: Dataset, Attribution, and Evaluation

The multiplayer online battle arena (MOBA) games have become increasingl...

14 Zelong Yang, et al. ∙

∙ 09/17/2020

Finding Influential Instances for Distantly Supervised Relation Extraction

Distant supervision has been demonstrated to be highly beneficial to enh...

11 Zifeng Wang, et al. ∙

∙ 09/06/2020

Online Disease Self-diagnosis with Inductive Heterogeneous Graph Convolutional Networks

We propose a Healthcare Graph Convolutional Network (HealGCN) to offer d...

17 Zifeng Wang, et al. ∙

∙ 09/06/2020

Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback

Counterfactual learning for dealing with missing-not-at-random data (MNA...

4 Zifeng Wang, et al. ∙

∙ 08/14/2020

Interpretable Real-Time Win Prediction for Honor of Kings, a Popular Mobile MOBA Esport

With the rapid prevalence and explosive development of MOBA esports (Mul...

0 Zelong Yang, et al. ∙

∙ 01/25/2020

On the Fairness of Randomized Trials for Recommendation With Heterogeneous Demographics and Beyond

Observed events in recommendation are consequence of the decisions made ...

1 Zifeng Wang, et al. ∙

∙ 12/03/2019

Less Is Better: Unweighted Data Subsampling via Influence Function

In the time of Big Data, training complex models on large-scale data set...

20 Zifeng Wang, et al. ∙

∙ 11/20/2019

On Universal Features for High-Dimensional Learning and Inference

We consider the problem of identifying universal low-dimensional feature...

0 Shao-Lun Huang, et al. ∙

∙ 10/28/2019

Reproducing Scientific Experiment with Cloud DevOps

The reproducibility of scientific experiment is vital for the advancemen...

0 Feng Zhao, et al. ∙

∙ 10/08/2019

An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data

In this paper, we propose an information-theoretic approach to design th...

0 Shao-Lun Huang, et al. ∙

∙ 06/30/2019

On the Sample Complexity of HGR Maximal Correlation Functions

The Hirschfeld-Gebelein-Rényi (HGR) maximal correlation and the correspo...

0 Shao-Lun Huang, et al. ∙

∙ 05/16/2019

An Information Theoretic Interpretation to Deep Neural Networks

It is commonly believed that the hidden layers of deep neural networks (...

0 Shao-Lun Huang, et al. ∙

∙ 11/22/2018

An Efficient Approach to Informative Feature Extraction from Multimodal Data

One primary focus in multimodal feature extraction is to find the repres...

0 Lichen Wang, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world